Effect of Incident Acoustic Pressure Amplitude on the Transmission Loss of Helmholtz Resonators
Bibliographic record
Abstract
Acoustic transmission loss is a common parameter utilized throughout several studies to evaluate the acoustic characteristics of a given test element. Transmission loss has been frequently referred to as a source independent parameter. However, this work presents evidence that the incident acoustic pressure amplitude does, in fact, have an effect on the measured transmission loss for some passive damping devices. The transmission loss was experimentally measured utilizing the two-source location method and the specimens tested include an expansion chamber, a quarter wave resonator, a Herschel–Quincke tube and various Helmholtz resonators. When varying the power supplied to the acoustic source, it was noted that all the devices exhibited nearly constant values of transmission loss, with the exception of the Helmholtz resonators. The Helmholtz resonators had a significant variance of transmission loss with respect to the acoustic source power. This decrease in performance is caused by the “jet-flow” phenomenon occurring at the Helmholtz resonator neck, which results in increased acoustic losses. The present work illustrates that the assumption of source independence, which is often made when using transmission loss to evaluate damping devices, must be taken with caution, as this assumption is case dependent and may be crucial when scaling experimental studies to an industrial setting.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".